Showing 7 of total 7 results (show query)
covaruber
sommer:Solving Mixed Model Equations in R
Structural multivariate-univariate linear mixed model solver for estimation of multiple random effects with unknown variance-covariance structures (e.g., heterogeneous and unstructured) and known covariance among levels of random effects (e.g., pedigree and genomic relationship matrices) (Covarrubias-Pazaran, 2016 <doi:10.1371/journal.pone.0156744>; Maier et al., 2015 <doi:10.1016/j.ajhg.2014.12.006>; Jensen et al., 1997). REML estimates can be obtained using the Direct-Inversion Newton-Raphson and Direct-Inversion Average Information algorithms for the problems r x r (r being the number of records) or using the Henderson-based average information algorithm for the problem c x c (c being the number of coefficients to estimate). Spatial models can also be fitted using the two-dimensional spline functionality available.
Maintained by Giovanny Covarrubias-Pazaran. Last updated 3 days ago.
average-informationmixed-modelsrcpparmadilloopenblascppopenmp
44 stars 12.63 score 300 scripts 10 dependents
scheike
timereg:Flexible Regression Models for Survival Data
Programs for Martinussen and Scheike (2006), `Dynamic Regression Models for Survival Data', Springer Verlag. Plus more recent developments. Additive survival model, semiparametric proportional odds model, fast cumulative residuals, excess risk models and more. Flexible competing risks regression including GOF-tests. Two-stage frailty modelling. PLS for the additive risk model. Lasso in the 'ahaz' package.
Maintained by Thomas Scheike. Last updated 7 months ago.
31 stars 10.42 score 289 scripts 44 dependents
cran
aod:Analysis of Overdispersed Data
Provides a set of functions to analyse overdispersed counts or proportions. Most of the methods are already available elsewhere but are scattered in different packages. The proposed functions should be considered as complements to more sophisticated methods such as generalized estimating equations (GEE) or generalized linear mixed effect models (GLMM).
Maintained by Renaud Lancelot. Last updated 1 years ago.
3 stars 5.15 score 15 dependents
aursiber
aods3:Analysis of Overdispersed Data using S3 Methods
Provides functions to analyse overdispersed counts or proportions. These functions should be considered as complements to more sophisticated methods such as generalized estimating equations (GEE) or generalized linear mixed effect models (GLMM). aods3 is an S3 re-implementation of the deprecated S4 package aod.
Maintained by Aurélie Siberchicot. Last updated 5 months ago.
2.94 score 38 scripts 1 dependents
m-signo
ptmixed:Poisson-Tweedie Generalized Linear Mixed Model
Fits the Poisson-Tweedie generalized linear mixed model described in Signorelli et al. (2021, <doi:10.1177/1471082X20936017>). Likelihood approximation based on adaptive Gauss Hermite quadrature rule.
Maintained by Mirko Signorelli. Last updated 3 years ago.
2.15 score 14 scriptscran
eba:Elimination-by-Aspects Models
Fitting and testing multi-attribute probabilistic choice models, especially the Bradley-Terry-Luce (BTL) model (Bradley & Terry, 1952 <doi:10.1093/biomet/39.3-4.324>; Luce, 1959), elimination-by-aspects (EBA) models (Tversky, 1972 <doi:10.1037/h0032955>), and preference tree (Pretree) models (Tversky & Sattath, 1979 <doi:10.1037/0033-295X.86.6.542>).
Maintained by Florian Wickelmaier. Last updated 4 years ago.
1.48 score 1 dependentscran
mdscore:Improved Score Tests for Generalized Linear Models
A set of functions to obtain modified score test for generalized linear models.
Maintained by Antonio Hermes M. da Silva-Junior. Last updated 8 years ago.
1.00 score